{"categories":[{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/5"}],"enrichment":{"capability":"Matscipy provides domain-specific computational tools for materials science simulations built on the Atomic Simulation Environment (ASE), covering plasticity, fracture mechanics, electro-chemistry, tribology, and elastic properties analysis.","skillfed_tags":["materials-simulation","atomic-scale-modeling","computational-materials"],"use_cases":["Simulate dislocation dynamics and plasticity in crystalline materials under stress.","Analyze fracture mechanics and crack propagation in atomic-scale models.","Calculate elastic properties (stiffness tensors, phonon modes) from atomic configurations.","Study tribological phenomena (friction, wear) at the atomic scale.","Compute neighbor lists and atomic strain fields efficiently for large systems.","Perform electro-chemistry simulations involving surface interactions and ion dynamics."],"what_it_does":"Matscipy is a Python library for materials science computation built on top of ASE (Atomic Simulation Environment). It provides domain-specific routines for modeling plasticity, dislocations, fracture mechanics, electro-chemistry, tribology, and elastic properties, along with low-level utilities like efficient neighbor lists, atomic strain calculation, ring analysis, and correlation functions. The library is designed for researchers and engineers who need to simulate and analyze atomic-scale material behavior; it wraps ASE's Atoms and Calculator objects to add specialized analysis and computation capabilities.\n\nThe package depends on numpy, scipy, ase, and packaging at runtime. Installation uses pre-built wheels on most platforms (Python 3.10\u20133.13, Windows/Linux/macOS), reducing compile friction, though source installation requires a working C compiler. The library is actively maintained (last commit August 2026) and marked Production/Stable, making it suitable for research workflows where reproducibility and domain-specific accuracy matter.","worth_installing":"Yes, if you are doing materials science research or simulation involving atomic-scale plasticity, fracture, tribology, or elastic property analysis. The library is actively maintained, has no known vulnerabilities, and provides specialized tools not easily replicated elsewhere. LGPL 2.1 licensing permits use in non-free code but requires source disclosure of modifications to matscipy itself. Medium install friction is acceptable given pre-built wheels; source compilation is only needed for development or unsupported platforms."},"id":"matscipy","links":{"html":"https://skillfed.io/packages/matscipy","md":"https://skillfed.io/packages/matscipy.md","pypi":"https://pypi.org/project/matscipy/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-11-20","license_spdx":null,"license_treatment":"copyleft","name":"matscipy","python_support":"supports_current","summary":"Generic Python Materials Science tools"},"popularity":{"monthly_downloads":219313,"position":9328,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.2.0"}